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http://dx.doi.org/10.1007/s43236-022-00495-x

On-line identifying stator winding short-circuit approach for a submersible motor based on faulty current monitoring  

Wang, Liguo (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Feng, Mingliang (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Tian, Zhenteng (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Bai, Yang (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Xu, Jianxin (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Wang, Zongjie (School of Electrical Engineering and Automation, Harbin Institute of Technology)
Publication Information
Journal of Power Electronics / v.22, no.11, 2022 , pp. 1872-1884 More about this Journal
Abstract
To monitor, diagnose, and suppress the inter-turn short-circuit faults (ITSCFs) of a submersible motor, an approach for the on-line identification of its winding faults has been proposed based on monitoring the stator current. First, an ITSCF model with the global leakage referred to the stator is given. With this model, the detection parameter, which is equal to the ratio of the turns of the fault windings to the total turns of the windings in the healthy phase, can be derived. Second, a faulty model described by the fourth order state-space equation of the motor with a winding fault has been given. Based on sampled stator voltage and stator current, the detection parameter has been solved and used to estimate the location and the turns of inter-turn short-circuit windings of the motor in real time. The accuracy and the robustness of the proposed approach has been illustrated with a 1.5 kW motor that is fed by a 10 kW inverter. Experiment shows that the identification accuracy in terms of the number of the ITSCF windings of the motor stator is less than 3. It can give a reference for the on-line diagnose the ITSCFs of the stator windings of a submersible motor that works in 2 km deep well.
Keywords
On-line estimation; Detection parameter; Inter-turn short-circuit fault; Submersible motor;
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Times Cited By KSCI : 4  (Citation Analysis)
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